Social Security Death Master File Research Articles

Healthcare Costs in Patients with Lethal Acute Graft-Versus-Host Disease (aGVHD) Post Allogeneic Hematopoietic Stem Cell Transplant (allo-HSCT) in the United States

Introduction Acute GVHD is a common complication and cause of death after allo-HSCT. Previous analysis showed that patients with aGVHD incurred significant healthcare costs (ie, average $33,675 monthly costs) over the first year post transplant in the US (Yu et al. Biol Blood Marrow Transplant. 2018; 24(3):S189–S190). Objective To estimate healthcare utilization and costs incurred among patients with aGVHD who died within 100 days or 1 year of aGVHD diagnosis in the United States. Method Administrative claims from the Optum Research Database were used to identify allo-HSCT patients from 01/01/10 to 08/31/16. Patients with aGVHD had ≥2 outpatient or ≥1 inpatient claims with diagnosis of aGVHD (International Classification of Disease [ICD]-9 279.51 or ICD-10 D89.810) within study period or until onset of cGVHD. Patients were included if ≥12 years old, enrolled in commercial or Medicare Advantage plan ≥6 months preceding and ≥360 days post-HSCT, or less if death occurred. Death was determined based on Social Security Death Master File data available for a portion of the patients in the database. Average per patient monthly all-cause healthcare costs while surviving were reported for patients with aGVHD who died within 100 days post-aGVHD diagnosis for the 100-day analysis, or died within 360 days for the 360-day analysis. Result Included in the analysis were 26 and 54 patients who died within 100 and 360-days after aGVHD diagnosis, respectively. Mean age was 57 years for both groups; and 46% and 44% were female, respectively. Patients with aGVHD who died within 100-days of aGVHD diagnosis had a median of 35 inpatient days (interquartile range [IQR]: 22-54) during median 44 day survival time from aGVHD diagnosis, and incurred $114,720 median (IQR: $52,744–$198,815) per-patient per-month costs for all-cause inpatient care while alive, accounting for 82% of median per-patient per-month all-cause total costs ($139,948; IQR: $91,793–$205,317). Patients who died within 1 year of aGVHD diagnosis had a median of 46 all-cause inpatient days (IQR 29-72) over a median 108-day survival time from aGVHD diagnosis and incurred $69,622 median (IQR: $26,823–$139,599) per-patient per-month costs for all-cause inpatient care while alive, accounting for 76% of per-patient per-month total costs (median $91,717; IQR: $43,893–$158,890). Conclusion Patients with aGVHD who survived less than 1 year post-diagnosis of aGVHD incurred substantial inpatient healthcare resource use and costs, which were mostly in the first 100 days of acute GVHD diagnosis. The economic burden associated with this high risk complication could be limited through early and effective therapies, resulting in fewer deaths and reduced in-patient care use.

Alive or dead: Validity of the Social Security Administration Death Master File after 2011.

To determine the reliability of the Social Security Death Master File (DMF) after the November 2011 changes limiting the inclusion of state records. Secondary data from the DMF, New York State (NYS) and New Jersey (NJ) Vital Statistics (VS), and institutional data warehouse. Retrospective study. Two cohorts: discharge date before November 1, 2011, (pre-2011) or after (post-2011). Death in-hospital used as gold standard. NYS VS used for out-of-hospital death. Sensitivity, specificity, Cohen's Kappa, and 1-year survival calculated. Patients matched to DMF using Social Security Number, or date of birth and Soundex algorithm. Patients matched to NY and NJ VS using probabilistic linking. 97069 patients January 2007-March 2016: 39075 pre-2011; 57994 post-2011. 3777 (3.9 percent) died in-hospital. DMF sensitivity for in-hospital death 88.9 percent (κ=0.93) pre-2011 vs 14.8 percent (κ=0.25) post-2011. DMF sensitivity for NY deaths 74.6 percent (κ=0.71) pre-2011 vs 26.6 percent (κ=0.33) post-2011. DMF sensitivity for NJ deaths 62.6 percent (κ=0.64) pre-2011 vs 10.8 percent (κ=0.15) post-2011. DMF sensitivity for out-of-hospital death 71.4 percent pre-2011 (κ=0.58) vs 28.9 percent post-2011 (κ=0.34). Post-2011, 1-year survival using DMF data was overestimated at 95.8 percent, vs 86.1 percent using NYS VS. The DMF is no longer a reliable source of death data. Researchers using the DMF may underestimate mortality.

Liver transplantation and waitlist mortality for HCC and non-HCC candidates following the 2015 HCC exception policy change.

Historically, exception points for hepatocellular carcinoma (HCC) led to higher transplant rates and lower waitlist mortality for HCC candidates compared to non-HCC candidates. As of October 2015, HCC candidates must wait 6months after initial application to obtain exception points; the impact of this policy remains unstudied. Using 2013-2017 SRTR data, we identified 39 350 adult, first-time, active waitlist candidates and compared deceased donor liver transplant (DDLT) rates and waitlist mortality/dropout for HCC versus non-HCC candidates before (October 8, 2013-October 7, 2015, prepolicy) and after (October 8, 2015-October 7, 2017, postpolicy) the policy change using Cox and competing risks regression, respectively. Compared to non-HCC candidates with the same calculated MELD, HCC candidates had a 3.6-fold higher rate of DDLT prepolicy (aHR=3.49 3.69 3.89 ) and a 2.2-fold higher rate of DDLT postpolicy (aHR=2.09 2.21 2.34 ). Compared to non-HCC candidates with the same allocation priority, HCC candidates had a 37% lower risk of waitlist mortality/dropout prepolicy (asHR=0.54 0.63 0.73 ) and a comparable risk of mortality/dropout postpolicy (asHR=0.81 0.95 1.11 ). Following the policy change, the DDLT advantage for HCC candidates remained, albeit dramatically attenuated, without any substantial increase in waitlist mortality/dropout. In the context of sickest-first liver allocation, the revised policy seems to have established allocation equity for HCC and non-HCC candidates.

Who can tolerate a marginal kidney? Predicting survival after deceased donor kidney transplant by donor-recipient combination.

The impact of donor quality on post-kidney transplant (KT) survival may vary by candidate condition. Characterizing this variation would increase access to KT without sacrificing outcomes. We developed a tool to estimate post-KT survival for combinations of donor quality and candidate condition. We studied deceased donor KT recipients (n=120818) and waitlisted candidates (n=376272) between 2005 and 2016 by using the Scientific Registry of Transplant Recipients. Donor quality and candidate condition were measured by using the Kidney Donor Profile Index (KDPI) and the Estimated Post Transplant Survival (EPTS) score. We estimated 5-year post-KT survival based on combinations of KDPI and EPTS score using random forest algorithms and waitlist survival by EPTS score using Weibull regressions. Survival benefit was defined as absolute reduction in mortality risk with KT. For candidates with an EPTSscore of80, 5-year waitlist survival was 47.6%, and 5-year post-KT survival was 78.9% after receiving kidneys with a KDPIof20 and was 70.7% after receiving kidneys with a KDPIof80. The impact of KDPI on survival benefit varied greatly by EPTS score. For candidates with low EPTS scores (eg, <40), the KDPI had limited impact on survival benefit. For candidates with middle or high EPTS scores (eg, >40), survival benefit decreased with higher KDPI but was still substantial even with a KDPIof100 (>16 percentage points). Our prediction tool (www.transplantmodels.com/kdpi-epts) can support individualized decision-making on kidney offers in clinical practice.

Ethnic and Age Disparities in Outcomes among Liver Transplant Waitlist Candidates

Background Despite the increasing prevalence of end-stage liver disease (ESLD) in older adults, there is no consensus to determine suitability for liver transplantation (LT) in the elderly. Disparities in LT access exist, with a disproportionately lower percentage of African Americans (AA) receiving LT. Understanding LT waitlist (WL) outcomes in older adults, specifically AA, will identify opportunities to improve LT access for this vulnerable population. Methods All adult, liver-only white and AA LT WL candidates (1/1/03-10/1/14) were identified in the Scientific Registry of Transplant Recipients. Age and race categories were defined as younger (age <60) white, younger AA, older (age ≥60) white, and older AA. Outcomes were delisting, transplantation, and WL mortality (supplemented by the Social Security Death Master File and Centers for Medicare and Medicaid Services). To account for underlying age and race differences in LT and WL mortality, outcomes were modeled using Fine and Gray competing risks. Results Among 93,458 candidates, 58.1% underwent LT, 14.9% died on the WL, and 20.2% were delisted. Among those delisted, 8.0% were later relisted, and 35.6% died. Outcomes did not differ for younger AA compared with younger whites. However, both older whites (sHR 1.05,95%CI 1.01-1.08) and older AA (sHR 1.13,95%CI 1.03-1.25) were more likely than younger whites to be delisted and to die after delisting (sHR 1.34,95%CI 1.27-1.42 and sHR 1.42,95%CI 1.23-1.63 respectively)(Table). Older whites (sHR 1.16,95%CI 1.12-1.22) were also more likely to die while listed than younger whites. Older AA had no increased risk of WL mortality but were less likely to undergo LT (sHR 0.92, 95%CI 0.86-0.97).Conclusion Independent of race, older LT candidates were more likely than younger whites to be delisted and to die after delisting. Older whites had higher WL mortality, while older AA were less likely to undergo LT. Our findings support the need for interventions to ensure medical suitability for LT among older adults and to address disparities in LT access for older AA. National Institutes of Health- National Research Service Award, through Grant Award Number T32 DK007545.

All-Cause Mortality for Life Insurance Applicants with a Family History of Coronary Artery Disease Before 60.

-To determine the all-cause mortality of life insurance applicants having a family history of coronary artery disease (CAD) before age 60. -Epidemiological studies have shown that a family history of premature CAD is an independent risk factor for CAD events. The strength of the association between family history and CAD is greatest with earlier age of presentation of CAD in the family member and when multiple family members are affected. Despite earlier insurance studies on this relationship, there is sparse current data on the association between family history of CAD and all-cause mortality in life insurance applicants. -Life insurance applicants with reported family history of Coronary Artery Disease (CAD) were extracted from data covering United States residents between October 2009 and October 2016. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2009 to 2012 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2009 to 2016 to determine vital status. Actual to Expected (A/E) mortality ratios were calculated using the Society of Actuaries 2015 Valuation Basic Table (2015VBT), select and ultimate table (age last birthday). All expected bases were not smoker distinct. Confidence bands around these mortality ratios were calculated. The variables of interest were applicant age, gender, number of family members with CAD before age 60, and the presence of cardiac or cardiovascular conditions. -Overall, the mortality of applicants with family members with a history of CAD before age 60 was slightly lower than expected mortality based on the 2015 VBT. Applicants with a cardiac or cardiovascular comorbid condition had a significantly higher mortality ratio. For applicants aged 25-54 and 65-75 with cardiac comorbid conditions, the mortality ratio was 2 times that of those without a cardiac comorbid condition. For those aged 55-64 with cardiovascular comorbid conditions, the mortality ratio was 2.9 times that of those without a cardiovascular comorbid condition. Females had a slightly higher mortality ratio for all age groups, number of family members with CAD before age 60, and cardiovascular conditions. -A family history of CAD before the age of 60 in an insurance applicant may be associated with increased all-cause mortality. Overall in this study, life insurance applicants had a mortality slightly lower than the expected mortality based on the 2015 VBT. However, applicants with a positive family history and a cardiac or cardiovascular comorbid condition had a significantly higher mortality ratio.

255 Long-Term Mortality in Pediatric Firearm Assault Survivors: A Retrospective, Multi-Center, Comparative Cohort Study

Children and youth in the United States face an inordinately high risk of firearm violence, but the long-term mortality risk of pediatric survivors of firearm assault is poorly understood. Therefore, we aimed to determine whether children surviving to hospital discharge after firearm assault are at increased risk of mortality and to elucidate the factors associated with later mortality. We performed a retrospective triple cohort study of pediatric patients aged 0 to 16 years seen at three trauma centers in Oakland and San Francisco, California between 2000 and 2009. By consecutively sampling from the trauma registries using International Classification of Diseases, Ninth Revision (ICD-9) E-codes, we constructed three cohorts comprised of all patients who presented for (1) firearm assault, (2) assault without firearm and (3) unintentional trauma. We excluded patients who were seen for suspected child abuse or suicide attempt. Additional demographic and clinical information was obtained from the medical record, including subsequent emergency department visits for trauma and gunshot wound. We queried the Social Security Death Master File and the California Department of Public Health Vital Statistics (2000-2014) to identify those who died after surviving their initial hospitalization and to determine cause of death. Cox proportional hazards regression was employed to determine hazard ratios, adjusting for demographic and clinical covariates. The trauma registry query yielded 413 firearm assault, 405 non-firearm assault, and 7062 non-assault-based trauma patients who survived their index emergency department visit and hospitalization. During a median follow-up of 8.2 years (inter-quartile range [IQR] 6.6-9.9 years), 9.0 years (IQR 7.1-11.6 years) and 9.3 years (IQR 7.1-11.8 years), a total of 75 deaths occurred, including 3.9% (n= 16), 3.2% (n= 13), and 0.7% (n= 46) of the three cohorts, respectively. Deaths occurred at a median age of 19.7 years and a median of 5.4 years after index injury. Two-thirds of all deaths following index visit (n= 50) were due to homicide. Adolescent age (adjusted hazard ratio [AHR] 2.9; 95% confidence interval [CI] 1.3-6.6), male sex (AHR 3.0; 95% CI 1.3-7.1), black race (AHR 3.3; 95% CI 1.2-9.4), and public insurance (AHR 2.5; 95% CI 1.2-5.2) were independent risk factors for long-term mortality. Firearm assault (AHR 1.8; 95% CI, 0.82-4.0) and non-firearm assault (AHR 1.9; 95% CI, 0.93-3.9) patients experienced increased risk of long-term mortality compared to non-assault trauma patients, although these differences did not reach statistical significance. Among adolescents aged 12 to 16 years, being assaulted (either with or without a firearm) was an independent risk factor for long-term mortality (AHR 1.9; 95% CI 1.01-3.6). Severe injury severity score, location of injury, and violent crime index by city of residence were not significant predictors of mortality. Among children seen in urban trauma centers, young adolescents who survive after exposure to assault, either with or without a firearm, have increased long-term mortality compared to those who survive unintentional, non-violent trauma. Given that most of these deaths are due to homicide, further studies are needed to identify effective methods of secondary prevention for this high-risk population.

Patterns and outcomes of traumatic pancreatic injuries: A retrospective review from a large multi-institutional healthcare system

Introduction Traumatic pancreatic injuries are rare, and morbidity and mortality information are often conflicting. To determine the frequency and outcomes of patients presenting with trauma to the pancreas, we reviewed data from a large multi-institutional healthcare system for mechanism of injury, intervention, subsequent complications, in-hospital morbidity rates, and mortality. Methods We performed a retrospective analysis of records of all pancreatic injury cases seen at four healthcare centers from 1990 to 2014. Descriptive measures are presented for continuous and categorical data. Mortality rates were obtained using the publicly accessible Social Security Death Master File. Results Of 69 patients with pancreatic injuries, median age was 24 years (range 1–88). Mechanisms of injury were blunt in 87% and penetrating in 11.8%. The median injury grade was 1. Most injuries involved the pancreatic head (24.6%). Median Injury Severity Score at presentation was 9. Thirty-seven (53.6%) patients required surgery. Twenty-five patients (36.2%) required total parenteral nutrition, 34 patients (49.3%) developed intra-abdominal fluid collections, 24 patients (34.8%) developed acute pancreatitis, and three (4.4%) developed endocrine insufficiency requiring insulin. Ten (14.5%) patients died. There were four (5.8%) readmissions and one re-operation (1.4%) within 30 days of discharge. Conclusion Traumatic pancreatic injuries occur most frequently in young healthy males with little or no comorbidities, and are generally associated with other acute injuries. Contrary to past reports, our results revealed a low mortality rate but significant morbidity, with the most common complications being intra-abdominal fluid collections, acute pancreatitis, and a need for total parenteral nutrition.

NT-proBNP Predicts All-Cause Mortality in a Population of Insurance Applicants, Follow-up Analysis and Further Observations.

- Further refine the independent value of NT-proBNP, accounting for the impact of other test results, in predicting all-cause mortality for individual life insurance applicants with and without heart disease. - Using the Social Security Death Master File and multivariate analysis, relative mortality was determined for 245,322 life insurance applicants ages 50 to 89 tested for NT-proBNP (almost all based on age and policy amount) along with other laboratory tests and measurement of blood pressure and BMI. - NT-proBNP values ≤75 pg/mL included the majority of applicants denying heart disease and had the lowest risk, while values >500 pg/mL for females and >300 pg/mL for males had very high relative risk. Those admitting to heart disease had a higher mortality risk for each band of NT-proBNP relative to those denying heart disease but had a similar and equally predictive risk curve. - NT-proBNP is a strong independent predictor of all-cause mortality in the absence or presence of known heart disease but the range of values associated with increased risk varies by sex.

Outcomes of Traumatic Pancreatic Injuries in Pediatric and Adult Patients: A Retrospective Study Involving Four Trauma Centers

AbstractTraumatic injuries of the pancreas are rare and affect both children and adults. Very little has been done to investigate differences in outcome between these two age groups. We performed a retrospective review of cases in four trauma hospitals to determine the differences in outcomes between pediatric and adult patients with traumatic pancreatic injuries. A retrospective chart review was performed for 69 pediatric and adult patients seen at four trauma centers in our health system between 1990 and 2014. The Mann–Whitney's U-test was used to compare continuous variables, while the chi-square and Fisher's exact tests were used for categorical variables. Mortality was determined using the Social Security Death Master File. In this study, 26 pediatric and 43 adult patients were included. Median ages were 11.4 and 42.3 years, respectively. There were significant differences in mechanism of blunt injury between pediatric and adults (motor vehicle collisions = 17.4 vs. 64.9%, bicycle accidents = 43.5 vs. 0.0%; p-value for both comparisons &lt; 0.0001), median injury severity score (6.5 vs. 12; p = 0.030), surgical management (30.8 vs. 67.4%; p = 0.003), and postinjury pancreatitis (57.7 vs. 20.9%; p = 0.002). Median hospital length of stay was 5 versus 11 days (p = 0.005), respectively. There were no differences in mortality or other complications. In spite of significant differences in blunt injury type, injury severity, and the need for surgery, there were no significant differences in mortality or most postinjury complications between pediatric and adult patients with traumatic pancreatic injuries.

All-Cause Mortality for Life Insurance Applicants with a History of Breast Cancer.

Breast cancer is the most commonly diagnosed cancer worldwide. Breast cancer is also the second leading cause of cancer death among women in the United States after lung cancer with over 40,000 breast cancer deaths occurring each year. The purpose of this research was to determine the all-cause mortality of applicants diagnosed with breast cancer currently or at some time in the past. Life insurance applicants with reported breast cancer were extracted from data covering United States residents between November 2007 and November 2014. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2007 to 2011 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2007 to 2014 to determine vital status. If there was a death from the other death source, then the SSDMF was searched to verify the death. The study had approximately 561,000 person-years of exposure. Actual-to-expected (A/E) mortality ratios were calculated using the Society of Actuaries 2008 Valuation Basic Table (2008VBT), select and ultimate table (age last birthday) and the 2010 US population as expected mortality ratios. Since the A/Es presented in this paper were known to be an underestimate due to the exclusion of the recent SSDMF deaths, comparative analysis of the mortality ratios was done. Since there was no smoking status information in this study, all expected bases were not smoker distinct. Overall, the 35-44 age group had 6.3 times the relative mortality ratio than those in the 65-75 age group. The relative mortality ratio for the 35-44 age group applicants, when cancer severity was accounted for in combination with 3 or more nodes of cancer involvement, was 29.3 times that when compared to those in the 65-75 age group having localized cancer, where no nodes are involved. The 35-44 age group applicants who were diagnosed with cancer within the last year had over 10-fold increase in relative mortality ratios compared to the 65-75 age group, who were over 10 years from diagnosis. Taking the severity of cancer along with time from diagnosis showed over a 12 times relative mortality ratio between the low rate of over 10 years from diagnosis and localized involvement to those diagnosed within the last year having 3 or more nodes with cancer. Applicant age, time since diagnosis and cancer severity were the most significant variables to predict the relative mortality ratios.

All-Cause Mortality for Life Insurance Applicants with a History of Prostate Cancer.

- To determine the all-cause mortality of life insurance applicants diagnosed with prostate cancer currently or at some time in the past. - Prostate cancer is common and a frequent cause of cancer death. Both the frequency of prostate cancer in men and its propensity for causing premature mortality require insurance company medical directors and underwriters to have a good understanding of prostate cancer-related mortality trends, patterns, and outcomes in the insured population. - Life insurance applicants with reported prostate cancer were extracted from data covering United States residents between November 2007 and November 2014. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2007 to 2011 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2007 to 2014 to determine vital status. Actual to Expected (A/E) mortality ratios were calculated using the Society of Actuaries 2015 Valuation Basic Table (2015VBT), select and ultimate table (age last birthday) and the 2013 US population as expected mortality ratios. All expected bases were not smoker distinct. - The study covered applicants between the ages of 45 and 75 and had approximately 405,000 person-years of exposure. Older aged applicants had a lower mortality ratio than those who were younger. Applicants 45 to 54 had the highest mortality ratios in the first year after diagnosis which steadily decreased in years 6 to 10 with an increase in the mortality ratio for those over 10 years from diagnosis. Relative mortality rate was close to unity for those with localized cancer across all age groups. The mortality ratio was 2 to 4 times greater for those with cancer in 1 positive node, and much greater with 3 positive nodes. For each time-from-diagnosis category, the relative mortality ratios compared to age were highest in the 45-54 age group. The A/E mortality ratios based on the 2015VBT were consistently 3 to 4 times that of the mortality ratios based on the 2013 US population. - The mortality patterns of insurance applicants with prostate cancer were similar to that observed in individuals with prostate cancer in the general population. Applicant age, time to diagnosis and cancer severity were the most significant variables to predict mortality.

Do inferences about mortality rates and disparities vary by source of mortality information?

PurposeResearchers who study mortality among survey participants have multiple options for obtaining information about which participants died (and when and how they died). Some use public record and commercial databases; others use the National Death Index; some use the Social Security Death Master File; and still others triangulate sources and use Internet searches and genealogic methods. We ask how inferences about mortality rates and disparities depend on the choice of source of mortality information. MethodsUsing data on a large, nationally representative cohort of people who were first interviewed as high school sophomores in 1980 and for whom we have extensive identifying information, we describe mortality rates and disparities through about age 50 using four separate sources of mortality data. We rely on cross-tabular and multivariate logistic regression models. ResultsThese sources of mortality information often disagree about which of our panelists died by about age 50 and also about overall mortality rates. However, differences in mortality rates (i.e., by sex, race/ethnicity, education) are similar across of sources of mortality data. ConclusionResearchers' source of mortality information affects estimates of overall mortality rates but not estimates of differential mortality by sex, race and/or ethnicity, or education.

Survival After Secondary Prevention Implantable Cardioverter-Defibrillator Placement

This study sought to define the characteristics and risks of death of patients receiving a physician-designated secondary prevention implantable cardioverter-defibrillator (ICD) in contemporary clinical practice. Data on utilization and outcomes of ICDs for the secondary prevention of sudden cardiac death (SCD) are limited. Patients enrolled in the National Cardiovascular Data Registry's (NCDR) ICD Registry from 2006 to 2009 with a physician-designated secondary prevention indication for ICD implantation were identified and linked to the Social Security Death Master File. Those patients with a history either of tachycardic arrest or sustained ventricular tachycardia (SCD/VT) or of syncope without SCD/VT were included. Kaplan-Meier survival analysis was used to assess mortality. Cox proportional hazards survival modeling was used to assess the risk of death in these groups, adjusting for patient characteristics. In the study cohort of 46,685 patients (mean age 66 ± 14 years, 73.5% male, 85% white), 78% had SCD/VT and 22% had syncope. Overall mortality was 10.4% at 1 year and 16.4% at 2 years. Compared with patients having SCD/VT, the adjusted hazard of death at 1 year was lower in the patients having syncope (hazard ratio: 0.89; 95%confidence interval: 0.83 to 0.96) but was not significantly different by 2 years (hazard ratio: 0.96; 95% confidence interval: 0.90 to 1.01). Nearly 9 of 10 patients receiving a secondary prevention ICD in clinical practice are alive 1 year after implantation. The risk of death varies by indication and is highest among patients who survive SCD or sustained VT inthefirst year after device implantation.

Prognostic Utility of the Braden Scale and the Morse Fall Scale in Hospitalized Patients With Heart Failure.

Geriatric syndromes are common in hospitalized elders with heart failure (HF), but association with clinical outcomes is not well characterized. The purpose of this study ( N = 289) was to assess presence of geriatric syndromes using Joint Commission-mandated measures, the Braden Scale (BS) and Morse Fall Scale (MFS), and to explore prognostic utility in hospitalized HF patients. Data extracted from the electronic medical record included sociodemographics, medications, clinical data, comorbid conditions, and the BS and MFS. The primary outcome of mortality was assessed using Social Security Death Master File. Statistical analysis included Cox proportional hazards models to assess association between BS and MFS scores and all-cause mortality with adjustment for known clinical prognostic factors. Higher risk BS and MFS scores were common in hospitalized HF patients, but were not independent predictors of survival. Further study of the clinical utility of these scores and other measures of geriatric syndromes in HF is warranted.

Heart Failure Readmission Reduction.

Little is known regarding effectiveness of readmission reduction programs over time. The Heart Failure Management Program (HFMP) of St. John's Physician Group Practice (PGP) Demonstration provided an opportunity to assess outcomes over an extended period. Data from an electronic health record, an inpatient database, a disease registry, and the Social Security Death Master File were analyzed for patients admitted with heart failure (HF) for 5 years before (Period 1) and 5 years after (Period 2) inception of PGP. HF admissions decreased (Period 1, 58.3/month; Period 2, 52.4/month, P = .007). Thirty-day all-cause readmission rate dropped from Period 1 (annual average 18.8% [668/3545]) to year 1 of Period 2 (16.9% [136/804], P = .04) and remained stable thereafter (annual average 16.8% [589/3503]). Thirty-day mortality rate was flat throughout. HFMP was associated with decreased readmissions, primarily related to outpatient case management, while mortality remained stable.

The reproducibility and prognostic value of serial measurements of heart rate response to regadenoson during myocardial perfusion imaging.

The heart rate response (HRR, percentage change from baseline) to regadenoson during myocardial perfusion imaging (MPI) can provide incremental prognostic value in patients with known or suspected coronary artery disease. Our purpose was to evaluate the variability and prognostic value of HRR on serial measurements. We studied 648 consecutive patients (61 ± 11years, 48% with diabetes) who underwent two regadenoson MPI studies (16 ± 9months between studies). HRR <30% was defined as abnormal. All-cause mortality was determined by chart review and verified using the US Social Security Death Master File. HRR was well correlated between the two studies (intraclass correlation coefficient 0.72, 95% CI 0.67 - 0.76) with no systematic bias (mean difference 0.88%, p = 0.2) or proportional bias (p = 0.5) by Bland-Altman analysis in all patients and in those with normal MPI on both studies. Of the 308 patients (48%) with normal baseline HRR (HRR-1), 33% had developed a blunted HRR on the second MPI study (HRR-2). Older age, male gender, end-stage renal disease, and abnormal baseline left ventricular ejection fraction were independent predictors of a new-onset abnormal HRR. During a mean follow-up of 2.4 ± 1.2years, 55 patients (8.5%) died. Patients with a blunted HRR-1 had increased mortality risk irrespective of their HRR-2 (p = 0.9, log-rank test). Among patients with normal HRR-1, a blunted HRR-2 was an independent predictor of all-cause mortality beyond clinical and traditional MPI data (hazard ratio 2.83, 95% CI 1.14 - 7.03). Finally, patients with a normal HRR-1 and HRR-2 had the lowest event rate, while those with any abnormal HRR had an increased risk of death (hazard ratio 2.5, 95% CI 1.2 - 5.4). There was good correlation in the HRR to regadenoson on serial measurements without systematic or proportional biases. Patients with consistently normal HRR had the best prognosis.

Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching.

Health information exchange (HIE) facilitates the exchange of patient information across different healthcare organizations. To match patient records across sites, HIEs usually rely on a master patient index (MPI), a database responsible for determining which medical records at different healthcare facilities belong to the same patient. A single patient's records may be improperly split across multiple profiles in the MPI. We investigated the how often two individuals shared the same first name, last name, and date of birth in the Social Security Death Master File (SSDMF), a US government database containing over 85 million individuals, to determine the feasibility of using exact matching as a split record detection tool. We demonstrated how a method based on exact record matching could be used to partially measure the degree of probable split patient records in the MPI of an HIE. We calculated the percentage of individuals who were uniquely identified in the SSDMF using first name, last name, and date of birth. We defined a measure consisting of the average number of unique identifiers associated with a given first name, last name, and date of birth. We calculated a reference value for this measure on a subsample of SSDMF data. We compared this measure value to data from a functioning HIE. We found that it was unlikely for two individuals to share the same first name, last name, and date of birth in a large US database including over 85 million individuals. 98.81% of individuals were uniquely identified in this dataset using only these three items. We compared the value of our measure on a subsample of Social Security data (1.00089) to that of HIE data (1.1238) and found a significant difference (t-test p-value < 0.001). This method may assist HIEs in detecting split patient records.

2014 CRL Build Study of Life Insurance Applicants.

Objective .- Determine the impact of build on insurance applicant mortality accounting for smoking, laboratory test values and blood pressure. Method .- The study consisted of 2,051,370 applicants tested at Clinical Reference Laboratory between 1993 and 2007 with build and cotinine measurements available whose body mass index (BMI) was between 15 and 47. Vital status was determined as of September, 2011 by the Social Security Death Master File. Excluded from the primary study were applicants with HbA1c values ≥6.5%, systolic BP ≥141 mmHg, albumin values ≤3.3 g/dL or total cholesterol values ≤130 mg/dL. Relative mortality was determined by Cox regression analysis for bands of BMI split by age, sex and smoking status (urine cotinine positive). Results .- A majority of applicants had BMI >24 (overweight or obese by WHO criteria). After the exclusions noted above, relative mortality does not increase by >34% unless BMI is <20 (<18 for female non-smokers age 18 to 59) or BMI is >34. BMI values in the range of 22 to 24 and 25 to 29, overall, had similar and the lowest relative risks. For most nonsmokers, risk was lowest in the lower of these two BMI bands but for smokers (and non-smoking males age 60 to 89) risk was lowest in the higher BMI band. Additional analysis showed limited reduction in relative risk by accounting for all laboratory test values as well as continuing the exclusions. Eliminating the exclusions resulted in only a modest increase in relative risk because the mortality rate of the reference band increased as well. Conclusion .- After excluding elevated HbA1c and blood pressure (associated with high BMI) and low albumin and cholesterol (associated with low BMI) which are usually evaluated separately, mortality varies by a limited degree for BMI 20 to 34. Accounting for the mortality impact of other test values, in addition to the exclusions noted, reduced mortality associated with high BMI to a limited extent, but had little impact on mortality associated with low BMI.

All-Cause Mortality for Diabetics or Individuals with Hyperglycemia Applying for Life Insurance.

Diabetics and individuals with lab results consistent with a diagnosis of diabetes or hyperglycemia were extracted from data covering US residents who applied for life insurance between January 2007 and January 2014. Information about these applicants was matched to the Social Security Death Master File (SSDMF) and another commercially available death source file to determine vital status. Due to the inconsistencies of reporting within the death files, there were two cohorts of death cases, one including the imputed year of birth (full cohort of deaths), and the second where the date of birth was known (reduced cohort of deaths). The study had approximately 8.5 million person-years of exposure. Actual to expected (A/E) mortality ratios were calculated using the Society of Actuaries 2008 Valuation Basic Table (2008VBT) select table, age last birthday and the 2010 US population as expected mortality rates. With the 2008VBT as an expected basis, the overall A/E mortality ratio was 3.15 for the full cohort of deaths and 2.56 for the reduced cohort of deaths. Using the US population as the expected basis, the overall A/E mortality ratio was 0.98 for the full cohort of deaths and 0.79 for the reduced cohort. Since there was no smoking status information in this study, all expected bases were not smoker distinct. A/E mortality ratios varied by disease treatment category and were considerably higher in individuals using insulin. A/E mortality ratios decreased with increasing age and took on a J-shaped distribution with increasing BMI (Body Mass Index). The lowest mortality ratios were observed for overweight and obese individuals. The A/E mortality ratio based on the 2008VBT decreased with the increase in applicant duration, which was defined as the time since initial life insurance application.